#practiceLinkDiv { display: none! importante; }Dato un array di n numeri interi. Il compito è rimuovere o eliminare il numero minimo di elementi dall'array in modo che quando gli elementi rimanenti vengono posizionati nello stesso ordine di sequenza per formare un sequenza ordinata crescente .
Esempi:
Input : {5 6 1 7 4}Recommended Practice Numero minimo di eliminazioni per creare una sequenza ordinata Provalo!
Output : 2
Removing 1 and 4
leaves the remaining sequence order as
5 6 7 which is a sorted sequence.
Input : {30 40 2 5 1 7 45 50 8}
Output : 4
UN soluzione semplice è rimuovere tutte le sottosequenze uno per uno e controlla se il gruppo rimanente di elementi è in ordine oppure no. La complessità temporale di questa soluzione è esponenziale.
UN approccio efficiente utilizza il concetto di trovare la lunghezza della sottosequenza crescente più lunga di una data sequenza.
Algoritmo:
--> arr be the given array.C++
--> n number of elements in arr .
--> len be the length of longest
increasing subsequence in arr .
-->// minimum number of deletions
min = n - len
// C++ implementation to find // minimum number of deletions // to make a sorted sequence #include using namespace std; /* lis() returns the length of the longest increasing subsequence in arr[] of size n */ int lis( int arr[] int n ) { int result = 0; int lis[n]; /* Initialize LIS values for all indexes */ for (int i = 0; i < n; i++ ) lis[i] = 1; /* Compute optimized LIS values in bottom up manner */ for (int i = 1; i < n; i++ ) for (int j = 0; j < i; j++ ) if ( arr[i] > arr[j] && lis[i] < lis[j] + 1) lis[i] = lis[j] + 1; /* Pick resultimum of all LIS values */ for (int i = 0; i < n; i++ ) if (result < lis[i]) result = lis[i]; return result; } // function to calculate minimum // number of deletions int minimumNumberOfDeletions(int arr[] int n) { // Find longest increasing // subsequence int len = lis(arr n); // After removing elements // other than the lis we // get sorted sequence. return (n - len); } // Driver Code int main() { int arr[] = {30 40 2 5 1 7 45 50 8}; int n = sizeof(arr) / sizeof(arr[0]); cout << 'Minimum number of deletions = ' << minimumNumberOfDeletions(arr n); return 0; }
Java // Java implementation to find // minimum number of deletions // to make a sorted sequence class GFG { /* lis() returns the length of the longest increasing subsequence in arr[] of size n */ static int lis( int arr[] int n ) { int result = 0; int[] lis = new int[n]; /* Initialize LIS values for all indexes */ for (int i = 0; i < n; i++ ) lis[i] = 1; /* Compute optimized LIS values in bottom up manner */ for (int i = 1; i < n; i++ ) for (int j = 0; j < i; j++ ) if ( arr[i] > arr[j] && lis[i] < lis[j] + 1) lis[i] = lis[j] + 1; /* Pick resultimum of all LIS values */ for (int i = 0; i < n; i++ ) if (result < lis[i]) result = lis[i]; return result; } // function to calculate minimum // number of deletions static int minimumNumberOfDeletions(int arr[] int n) { // Find longest // increasing subsequence int len = lis(arr n); // After removing elements // other than the lis we get // sorted sequence. return (n - len); } // Driver Code public static void main (String[] args) { int arr[] = {30 40 2 5 1 7 45 50 8}; int n = arr.length; System.out.println('Minimum number of' + ' deletions = ' + minimumNumberOfDeletions(arr n)); } } /* This code is contributed by Harsh Agarwal */
Python3 # Python3 implementation to find # minimum number of deletions to # make a sorted sequence # lis() returns the length # of the longest increasing # subsequence in arr[] of size n def lis(arr n): result = 0 lis = [0 for i in range(n)] # Initialize LIS values # for all indexes for i in range(n): lis[i] = 1 # Compute optimized LIS values # in bottom up manner for i in range(1 n): for j in range(i): if ( arr[i] > arr[j] and lis[i] < lis[j] + 1): lis[i] = lis[j] + 1 # Pick resultimum # of all LIS values for i in range(n): if (result < lis[i]): result = lis[i] return result # Function to calculate minimum # number of deletions def minimumNumberOfDeletions(arr n): # Find longest increasing # subsequence len = lis(arr n) # After removing elements # other than the lis we # get sorted sequence. return (n - len) # Driver Code arr = [30 40 2 5 1 7 45 50 8] n = len(arr) print('Minimum number of deletions = ' minimumNumberOfDeletions(arr n)) # This code is contributed by Anant Agarwal.
C# // C# implementation to find // minimum number of deletions // to make a sorted sequence using System; class GfG { /* lis() returns the length of the longest increasing subsequence in arr[] of size n */ static int lis( int []arr int n ) { int result = 0; int[] lis = new int[n]; /* Initialize LIS values for all indexes */ for (int i = 0; i < n; i++ ) lis[i] = 1; /* Compute optimized LIS values in bottom up manner */ for (int i = 1; i < n; i++ ) for (int j = 0; j < i; j++ ) if ( arr[i] > arr[j] && lis[i] < lis[j] + 1) lis[i] = lis[j] + 1; /* Pick resultimum of all LIS values */ for (int i = 0; i < n; i++ ) if (result < lis[i]) result = lis[i]; return result; } // function to calculate minimum // number of deletions static int minimumNumberOfDeletions( int []arr int n) { // Find longest increasing // subsequence int len = lis(arr n); // After removing elements other // than the lis we get sorted // sequence. return (n - len); } // Driver Code public static void Main (String[] args) { int []arr = {30 40 2 5 1 7 45 50 8}; int n = arr.Length; Console.Write('Minimum number of' + ' deletions = ' + minimumNumberOfDeletions(arr n)); } } // This code is contributed by parashar.
JavaScript <script> // javascript implementation to find // minimum number of deletions // to make a sorted sequence /* lis() returns the length of the longest increasing subsequence in arr[] of size n */ function lis(arrn) { let result = 0; let lis= new Array(n); /* Initialize LIS values for all indexes */ for (let i = 0; i < n; i++ ) lis[i] = 1; /* Compute optimized LIS values in bottom up manner */ for (let i = 1; i < n; i++ ) for (let j = 0; j < i; j++ ) if ( arr[i] > arr[j] && lis[i] < lis[j] + 1) lis[i] = lis[j] + 1; /* Pick resultimum of all LIS values */ for (let i = 0; i < n; i++ ) if (result < lis[i]) result = lis[i]; return result; } // function to calculate minimum // number of deletions function minimumNumberOfDeletions(arrn) { // Find longest increasing // subsequence let len = lis(arrn); // After removing elements // other than the lis we // get sorted sequence. return (n - len); } let arr = [30 40 2 5 17 45 50 8]; let n = arr.length; document.write('Minimum number of deletions = ' + minimumNumberOfDeletions(arrn)); // This code is contributed by vaibhavrabadiya117. </script>
PHP // PHP implementation to find // minimum number of deletions // to make a sorted sequence /* lis() returns the length of the longest increasing subsequence in arr[] of size n */ function lis( $arr $n ) { $result = 0; $lis[$n] = 0; /* Initialize LIS values for all indexes */ for ($i = 0; $i < $n; $i++ ) $lis[$i] = 1; /* Compute optimized LIS values in bottom up manner */ for ($i = 1; $i < $n; $i++ ) for ($j = 0; $j < $i; $j++ ) if ( $arr[$i] > $arr[$j] && $lis[$i] < $lis[$j] + 1) $lis[$i] = $lis[$j] + 1; /* Pick resultimum of all LIS values */ for ($i = 0; $i < $n; $i++ ) if ($result < $lis[$i]) $result = $lis[$i]; return $result; } // function to calculate minimum // number of deletions function minimumNumberOfDeletions($arr $n) { // Find longest increasing // subsequence $len = lis($arr $n); // After removing elements // other than the lis we // get sorted sequence. return ($n - $len); } // Driver Code $arr = array(30 40 2 5 1 7 45 50 8); $n = sizeof($arr) / sizeof($arr[0]); echo 'Minimum number of deletions = ' minimumNumberOfDeletions($arr $n); // This code is contributed by nitin mittal. ?> Produzione
Minimum number of deletions = 4
Complessità temporale: SU2)
Spazio ausiliario: SU)
La complessità temporale può essere ridotta a O(nlogn) trovando il Dimensione della sottosequenza crescente più lunga (N Log N)
Questo articolo è stato fornito da Ayush Jauhari .
Approccio n. 2: utilizzare la sottosequenza crescente più lunga
Un approccio per risolvere questo problema è trovare la lunghezza della sottosequenza crescente più lunga (LIS) dell'array dato e sottrarla dalla lunghezza dell'array. La differenza ci dà il numero minimo di cancellazioni richieste per rendere ordinato l'array.
Algoritmo
1. Calcolare la lunghezza della sottosequenza crescente (LIS) più lunga dell'array.
2. Sottrarre la lunghezza del LIS dalla lunghezza dell'array.
3. Restituire la differenza ottenuta nel passaggio 2 come output.
#include #include #include // Required for max_element using namespace std; // Function to find the minimum number of deletions int minDeletions(vector<int> arr) { int n = arr.size(); vector<int> lis(n 1); // Initialize LIS array with 1 // Calculate LIS values for (int i = 1; i < n; ++i) { for (int j = 0; j < i; ++j) { if (arr[i] > arr[j]) { lis[i] = max(lis[i] lis[j] + 1); // Update LIS value } } } // Find the maximum length of LIS int maxLength = *max_element(lis.begin() lis.end()); // Return the minimum number of deletions return n - maxLength; } //Driver code int main() { vector<int> arr = {5 6 1 7 4}; // Call the minDeletions function and print the result cout << minDeletions(arr) << endl; return 0; }
Java import java.util.Arrays; public class Main { public static int minDeletions(int[] arr) { int n = arr.length; int[] lis = new int[n]; Arrays.fill(lis 1); // Initialize the LIS array with all 1's for (int i = 1; i < n; i++) { for (int j = 0; j < i; j++) { if (arr[i] > arr[j]) { lis[i] = Math.max(lis[i] lis[j] + 1); } } } return n - Arrays.stream(lis).max().getAsInt(); // Return the number of elements to delete } public static void main(String[] args) { int[] arr = {5 6 1 7 4}; System.out.println(minDeletions(arr)); // Output: 2 } }
Python3 def min_deletions(arr): n = len(arr) lis = [1] * n for i in range(1 n): for j in range(i): if arr[i] > arr[j]: lis[i] = max(lis[i] lis[j] + 1) return n - max(lis) arr = [5 6 1 7 4] print(min_deletions(arr))
C# using System; using System.Collections.Generic; using System.Linq; namespace MinDeletionsExample { class Program { static int MinDeletions(List<int> arr) { int n = arr.Count; List<int> lis = Enumerable.Repeat(1 n).ToList(); // Initialize LIS array with 1 // Calculate LIS values for (int i = 1; i < n; ++i) { for (int j = 0; j < i; ++j) { if (arr[i] > arr[j]) { lis[i] = Math.Max(lis[i] lis[j] + 1); // Update LIS value } } } // Find the maximum length of LIS int maxLength = lis.Max(); // Return the minimum number of deletions return n - maxLength; } // Driver Code static void Main(string[] args) { List<int> arr = new List<int> { 5 6 1 7 4 }; // Call the MinDeletions function and print the result Console.WriteLine(MinDeletions(arr)); // Keep console window open until a key is pressed Console.ReadKey(); } } }
JavaScript function minDeletions(arr) { let n = arr.length; let lis = new Array(n).fill(1); for (let i = 1; i < n; i++) { for (let j = 0; j < i; j++) { if (arr[i] > arr[j]) { lis[i] = Math.max(lis[i] lis[j] + 1); } } } return n - Math.max(...lis); } let arr = [5 6 1 7 4]; console.log(minDeletions(arr));
Produzione
2
Complessità temporale: O(n^2) dove n è la lunghezza dell'array
Complessità spaziale: O(n) dove n è la lunghezza dell'array
Approccio n. 3: utilizzo della ricerca binaria
Questo approccio utilizza la ricerca binaria per trovare la posizione corretta per inserire un dato elemento nella sottosequenza.
Algoritmo
1. Inizializzare una lista 'sub' con il primo elemento della lista di input.
2. Per ogni elemento successivo nell'elenco di input, se è maggiore dell'ultimo elemento in 'sub', aggiungilo a 'sub'.
3. Altrimenti usa la ricerca binaria per trovare la posizione corretta per inserire l'elemento in 'sub'.
4. Il numero minimo di eliminazioni richieste è pari alla lunghezza dell'elenco di input meno la lunghezza di 'sub'.
#include #include using namespace std; // Function to find the minimum number of deletions to make a strictly increasing subsequence int minDeletions(vector<int>& arr) { int n = arr.size(); vector<int> sub; // Stores the longest increasing subsequence sub.push_back(arr[0]); // Initialize the subsequence with the first element of the array for (int i = 1; i < n; i++) { if (arr[i] > sub.back()) { // If the current element is greater than the last element of the subsequence // it can be added to the subsequence to make it longer. sub.push_back(arr[i]); } else { int index = -1; // Initialize index to -1 int val = arr[i]; // Current element value int l = 0 r = sub.size() - 1; // Initialize left and right pointers for binary search // Binary search to find the index where the current element can be placed in the subsequence while (l <= r) { int mid = (l + r) / 2; // Calculate the middle index if (sub[mid] >= val) { index = mid; // Update the index if the middle element is greater or equal to the current element r = mid - 1; // Move the right pointer to mid - 1 } else { l = mid + 1; // Move the left pointer to mid + 1 } } if (index != -1) { sub[index] = val; // Replace the element at the found index with the current element } } } // The minimum number of deletions is equal to the difference between the input array size and the size of the longest increasing subsequence return n - sub.size(); } int main() { vector<int> arr = {30 40 2 5 1 7 45 50 8}; int output = minDeletions(arr); cout << output << endl; return 0; }
Java import java.util.ArrayList; public class Main { // Function to find the minimum number of deletions to make a strictly increasing subsequence static int minDeletions(ArrayList<Integer> arr) { int n = arr.size(); ArrayList<Integer> sub = new ArrayList<>(); // Stores the longest increasing subsequence sub.add(arr.get(0)); // Initialize the subsequence with the first element of the array for (int i = 1; i < n; i++) { if (arr.get(i) > sub.get(sub.size() - 1)) { // If the current element is greater than the last element of the subsequence // it can be added to the subsequence to make it longer. sub.add(arr.get(i)); } else { int index = -1; // Initialize index to -1 int val = arr.get(i); // Current element value int l = 0 r = sub.size() - 1; // Initialize left and right pointers for binary search // Binary search to find the index where the current element can be placed in the subsequence while (l <= r) { int mid = (l + r) / 2; // Calculate the middle index if (sub.get(mid) >= val) { index = mid; // Update the index if the middle element is greater or equal to the current element r = mid - 1; // Move the right pointer to mid - 1 } else { l = mid + 1; // Move the left pointer to mid + 1 } } if (index != -1) { sub.set(index val); // Replace the element at the found index with the current element } } } // The minimum number of deletions is equal to the difference between the input array size and the size of the longest increasing subsequence return n - sub.size(); } public static void main(String[] args) { ArrayList<Integer> arr = new ArrayList<>(); arr.add(30); arr.add(40); arr.add(2); arr.add(5); arr.add(1); arr.add(7); arr.add(45); arr.add(50); arr.add(8); int output = minDeletions(arr); System.out.println(output); } }
Python3 def min_deletions(arr): def ceil_index(sub val): l r = 0 len(sub)-1 while l <= r: mid = (l + r) // 2 if sub[mid] >= val: r = mid - 1 else: l = mid + 1 return l sub = [arr[0]] for i in range(1 len(arr)): if arr[i] > sub[-1]: sub.append(arr[i]) else: sub[ceil_index(sub arr[i])] = arr[i] return len(arr) - len(sub) arr = [30 40 2 5 1 7 45 50 8] output = min_deletions(arr) print(output)
C# using System; using System.Collections.Generic; class Program { // Function to find the minimum number of deletions to make a strictly increasing subsequence static int MinDeletions(List<int> arr) { int n = arr.Count; List<int> sub = new List<int>(); // Stores the longest increasing subsequence sub.Add(arr[0]); // Initialize the subsequence with the first element of the array for (int i = 1; i < n; i++) { if (arr[i] > sub[sub.Count - 1]) { // If the current element is greater than the last element of the subsequence // it can be added to the subsequence to make it longer. sub.Add(arr[i]); } else { int index = -1; // Initialize index to -1 int val = arr[i]; // Current element value int l = 0 r = sub.Count - 1; // Initialize left and right // pointers for binary search // Binary search to find the index where the current element // can be placed in the subsequence while (l <= r) { int mid = (l + r) / 2; // Calculate the middle index if (sub[mid] >= val) { index = mid; // Update the index if the middle element is // greater or equal to the current element r = mid - 1; // Move the right pointer to mid - 1 } else { l = mid + 1; // Move the left pointer to mid + 1 } } if (index != -1) { sub[index] = val; // Replace the element at the found index // with the current element } } } // The minimum number of deletions is equal to the difference // between the input list size and the size of the // longest increasing subsequence return n - sub.Count; } // Driver code static void Main() { List<int> arr = new List<int> { 30 40 2 5 1 7 45 50 8 }; int output = MinDeletions(arr); Console.WriteLine(output); Console.ReadLine(); } }
JavaScript // Function to find the minimum number of deletions to make a strictly increasing subsequence function minDeletions(arr) { let n = arr.length; let sub = []; // Stores the longest increasing subsequence sub.push(arr[0]); // Initialize the subsequence with the first element of the array for (let i = 1; i < n; i++) { if (arr[i] > sub[sub.length - 1]) { // If the current element is greater than the last element of the subsequence // it can be added to the subsequence to make it longer. sub.push(arr[i]); } else { let index = -1; // Initialize index to -1 let val = arr[i]; // Current element value let l = 0 r = sub.length - 1; // Initialize left and right pointers for binary search // Binary search to find the index where the current element can be placed // in the subsequence while (l <= r) { let mid = Math.floor((l + r) / 2); // Calculate the middle index if (sub[mid] >= val) { index = mid; // Update the index if the middle element is greater //or equal to the current element r = mid - 1; // Move the right pointer to mid - 1 } else { l = mid + 1; // Move the left pointer to mid + 1 } } if (index !== -1) { sub[index] = val; // Replace the element at the found index with the current element } } } // The minimum number of deletions is equal to the difference //between the input array size and the size of the longest increasing subsequence return n - sub.length; } let arr = [30 40 2 5 1 7 45 50 8]; let output = minDeletions(arr); console.log(output);
Produzione
4
Complessità temporale: O(n log n)
Spazio ausiliario: O(n)
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